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Resource allocation procedures for unknown sales response functions with additive disturbances

Author

Listed:
  • Daniel Gahler

    (University of Regensburg)

  • Harald Hruschka

    (University of Regensburg)

Abstract

We develop a modified exploration–exploitation algorithm which allocates a fixed resource (e.g., a fixed budget) to several units with the objective to attain maximum sales. This algorithm does not require knowledge of the form and the parameters of sales response functions and is able to cope with additive random disturbances. Note that additive random disturbances, as a rule, are a component of sales response functions estimated by econometric methods. We compare the developed algorithm to three rules of thumb which in practice are often used to solve this allocation problem. The comparison is based on a Monte Carlo simulation for 384 experimental constellations, which are obtained from four function types, four procedures (including our algorithm), similar/varied elasticities, similar/varied saturations, high/low budgets, and three disturbance levels. A statistical analysis of the simulation results shows that across a multi-period planning horizon the algorithm performs better than the rules of thumb considered with respect to two sales-related criteria.

Suggested Citation

  • Daniel Gahler & Harald Hruschka, 2022. "Resource allocation procedures for unknown sales response functions with additive disturbances," Journal of Business Economics, Springer, vol. 92(6), pages 997-1034, August.
    • Handle: RePEc:spr:jbecon:v:92:y:2022:i:6:d:10.1007_s11573-021-01077-2
    DOI: 10.1007/s11573-021-01077-2
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    References listed on IDEAS

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    1. Prabhakant Sinha & Andris A. Zoltners, 2001. "Sales-Force Decision Models: Insights from 25 Years of Implementation," Interfaces, INFORMS, vol. 31(3_supplem), pages 8-44, June.
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Marketing resource allocation; Exploration–exploitation algorithm; Monte Carlo simulation; Optimization;
    All these keywords.

    JEL classification:

    • M30 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - General
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

    Statistics

    Access and download statistics

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